I would rather guess that this is related to a small n_estimators. I
would try increasing n_estimators in the random forests.
G
On Thu, Apr 13, 2017 at 02:41:15PM -0400, Sebastian Raschka wrote:
> Hi,
> Have you tried to set numpy.set_printoptions(precision=8) ? Maybe that helps
> already.
> Best,
> Sebastian
> Sent from my iPhone
> On Apr 13, 2017, at 1:54 PM, Suranga Kasthurirathne <suranga...@gmail.com>
> wrote:
> Hi all,
> I'm using scikit-learn to build a number of random forrest models using
> the
> default number of trees.
> However, when I print out the prediction probability (http://
> scikit-learn.org/stable/modules/generated/
> sklearn.ensemble.RandomForestClassifier.html#
> sklearn.ensemble.RandomForestClassifier.predict_proba) for each outcome,
> its presented to me as a single decimal point (0.1, 0.2, 0.5 etc.). Only
> perhaps 5% of the data has more than a single decimal point.
> Is this normal behavior? is there some way I can increase the number of
> decimal points in the prediction probability outcomes? why arent I seeing
> more probabilities such as 0.231, 0.55551, 0.462156 etc.?
--
Gael Varoquaux
Researcher, INRIA Parietal
NeuroSpin/CEA Saclay , Bat 145, 91191 Gif-sur-Yvette France
Phone: ++ 33-1-69-08-79-68
http://gael-varoquaux.info http://twitter.com/GaelVaroquaux
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